Effects of Bisphenol A and Diethylstilbestrol on Estrogen Receptor Expression and Male Fertility
Bibliographic record
Abstract
Infertility is defined as a couple’s inability to conceive after one year of unprotected intercourse. Male reproductive pathologies are the predominate cause of at least 20% of cases of infertility; making male infertility is an important issue in overall population health. Endocrine disrupting chemicals (EDCs) can impair spermatogenesis by creating hormonal imbalances and morphological changes. DES and BPA are both exogenous estrogens, also known as xenoestrogens. Estrogen has an important role in fertility of males as well as females: it has a role in the overall endocrine balance required to allow spermatogenesis. Effects on the hypothalamic-pituitary-gonadal axis may be monitored by assessing for upregulation of estrogen receptors α and -B (ERα and ERβ), as well as the novel estrogen receptor g-protein coupled receptor 30 (GPR30). Controversy surrounds the mechanisms endocrine disruption associated with these chemicals, and whether the negative effects on fertility are relevant at low doses, or only at high doses which are systemically toxic. Analysis of literature associated with this ongoing research will enrich our understanding of the molecular bases for impairment of spermatogenesis and male fertility associated with exposure to EDCs, specifically DES and BPA. Once completed, this study will contribute to knowledge in the fields of population health, environmental health, and molecular genetics. With a more thorough understanding of the impact of EDCs on fertility, it is hoped that governments will further prevent exposure by better regulating the use of compounds such as DES and BPA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".